Various social media platforms are sources of valuable data containing social conversations and public expressions/opinions about product and/or services in the public domain. This social data provides an opportunity to monitor public opinion about the product and/or service under consideration and utilize the monitoring results to effectively engage with consumers of the product and/or service under consideration.
Current solutions include a searching method that searches and analyzes all documents on the fly and searches for a match with a query. However, these searching methods are not efficient. Also, they are not sufficient for effective monitoring and analysis of social media documents due to the nature of social media documents. Social media documents are often unstructured, noisy, contain complex expressions of sentiments, are usually verbose and deal with multiple topics. Thus, only a small portion of the social media documents may be relevant, but the search algorithm may return the entire document.